Jaesung Huh
- Artificial Intelligence top 5%
- Signal Processing top 2%
- Computer Vision and Pattern Recognition
- Computational Mechanics
- Mechanical Engineering
- Co-authors
- Joon Son ChungAndrew ZissermanSeongkyu MunSoyeon ChoeBong‐Jin LeeMinjae LeeSunghwan JungTengda Han
- Topics
- Speech and Audio Processing (12 papers)Music and Audio Processing (11 papers)Speech Recognition and Synthesis (11 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceEnergiesIEEE Journal of Selected Topics in Signal Processing
- Partner nations
- South KoreaUnited KingdomCzechia
In The Last Decade
Jaesung Huh
20 papers receiving 533 citations
Hit Papers
Peers
Comparison fields: 5 of 63
- Artificial Intelligence 425
- Signal Processing 378
- Computer Vision and Pattern Recognition 57
- Computational Mechanics 32
- Mechanical Engineering 29
Countries citing papers authored by Jaesung Huh
This map shows the geographic impact of Jaesung Huh's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jaesung Huh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jaesung Huh more than expected).
Fields of papers citing papers by Jaesung Huh
This network shows the impact of papers produced by Jaesung Huh. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jaesung Huh. The network helps show where Jaesung Huh may publish in the future.
Co-authorship network of co-authors of Jaesung Huh
This figure shows the co-authorship network connecting the top 25 collaborators of Jaesung Huh. A scholar is included among the top collaborators of Jaesung Huh based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jaesung Huh. Jaesung Huh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 10 | |
| 4 | 3 | |
| 5 | 17 | |
| 6 | 73 | |
| 7 | 5 | |
| 8 | 13 | |
| 9 | 4 | |
| 10 | 8 | |
| 11 | Playing a part: speaker verification at the movies | 12 |
| 12 | 1 | |
| 13 | 70 | |
| 14 | In Defence of Metric Learning for Speaker Recognitionbreakdown → | 232 |
| 15 | 26 | |
| 16 | 35 | |
| 17 | 14 | |
| 18 | 5 | |
| 19 | 1 | |
| 20 | 3 |
About Jaesung Huh
Jaesung Huh is a scholar working on Signal Processing, Statistics, Probability and Uncertainty and Artificial Intelligence, having authored 24 papers that have together received 556 indexed citations. Recurring topics across this work include Speech and Audio Processing (12 papers), Music and Audio Processing (11 papers) and Speech Recognition and Synthesis (11 papers). The work is most often cited by research in Signal Processing (378 citations), Artificial Intelligence (425 citations) and Computer Vision and Pattern Recognition (57 citations). Jaesung Huh has collaborated with scholars based in South Korea, United Kingdom and Czechia. Frequent co-authors include Joon Son Chung, Andrew Zisserman, Seongkyu Mun, Soyeon Choe, Bong‐Jin Lee, Minjae Lee, Sunghwan Jung, Tengda Han, Max Bain and Arsha Nagrani. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Energies and IEEE Journal of Selected Topics in Signal Processing.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.